# ordinal v2019.4-25

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## Regression Models for Ordinal Data

Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.

## Vignettes of ordinal

 Name static_figs/fig-fig2.pdf static_figs/fig-figEqui.pdf static_figs/fig-figFlex.pdf static_figs/fig-figNom2.pdf static_figs/fig-figSca.pdf clm_article.Rnw clm_article_refs.bib clmm2_tutorial.Rnw ordinal.bib No Results!